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<div class="subTitle">org.apache.spark.mllib.optimization</div>
<h2 title="Class LBFGS" class="title">Class LBFGS</h2>
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<li>java.lang.Object</li>
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<li>org.apache.spark.mllib.optimization.LBFGS</li>
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<dt>All Implemented Interfaces:</dt>
<dd>java.io.Serializable, <a href="../../../../../org/apache/spark/Logging.html" title="interface in org.apache.spark">Logging</a>, <a href="../../../../../org/apache/spark/mllib/optimization/Optimizer.html" title="interface in org.apache.spark.mllib.optimization">Optimizer</a></dd>
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<pre>public class <span class="strong">LBFGS</span>
extends java.lang.Object
implements <a href="../../../../../org/apache/spark/mllib/optimization/Optimizer.html" title="interface in org.apache.spark.mllib.optimization">Optimizer</a>, <a href="../../../../../org/apache/spark/Logging.html" title="interface in org.apache.spark">Logging</a></pre>
<div class="block">:: DeveloperApi ::
Class used to solve an optimization problem using Limited-memory BFGS.
Reference: <code>http://en.wikipedia.org/wiki/Limited-memory_BFGS</code>
param: gradient Gradient function to be used.
param: updater Updater to be used to update weights after every iteration.</div>
<dl><dt><span class="strong">See Also:</span></dt><dd><a href="../../../../../serialized-form.html#org.apache.spark.mllib.optimization.LBFGS">Serialized Form</a></dd></dl>
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<td class="colOne"><code><strong><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#LBFGS(org.apache.spark.mllib.optimization.Gradient, org.apache.spark.mllib.optimization.Updater)">LBFGS</a></strong>(<a href="../../../../../org/apache/spark/mllib/optimization/Gradient.html" title="class in org.apache.spark.mllib.optimization">Gradient</a> gradient,
<a href="../../../../../org/apache/spark/mllib/optimization/Updater.html" title="class in org.apache.spark.mllib.optimization">Updater</a> updater)</code> </td>
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<tr>
<th class="colFirst" scope="col">Modifier and Type</th>
<th class="colLast" scope="col">Method and Description</th>
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<tr class="altColor">
<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#optimize(org.apache.spark.rdd.RDD, org.apache.spark.mllib.linalg.Vector)">optimize</a></strong>(<a href="../../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple2<java.lang.Object,<a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a>>> data,
<a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a> initialWeights)</code>
<div class="block">Solve the provided convex optimization problem.</div>
</td>
</tr>
<tr class="rowColor">
<td class="colFirst"><code>static scala.Tuple2<<a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a>,double[]></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#runLBFGS(org.apache.spark.rdd.RDD, org.apache.spark.mllib.optimization.Gradient, org.apache.spark.mllib.optimization.Updater, int, double, int, double, org.apache.spark.mllib.linalg.Vector)">runLBFGS</a></strong>(<a href="../../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple2<java.lang.Object,<a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a>>> data,
<a href="../../../../../org/apache/spark/mllib/optimization/Gradient.html" title="class in org.apache.spark.mllib.optimization">Gradient</a> gradient,
<a href="../../../../../org/apache/spark/mllib/optimization/Updater.html" title="class in org.apache.spark.mllib.optimization">Updater</a> updater,
int numCorrections,
double convergenceTol,
int maxNumIterations,
double regParam,
<a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a> initialWeights)</code>
<div class="block">Run Limited-memory BFGS (L-BFGS) in parallel.</div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#setConvergenceTol(double)">setConvergenceTol</a></strong>(double tolerance)</code>
<div class="block">Set the convergence tolerance of iterations for L-BFGS.</div>
</td>
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<tr class="rowColor">
<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#setGradient(org.apache.spark.mllib.optimization.Gradient)">setGradient</a></strong>(<a href="../../../../../org/apache/spark/mllib/optimization/Gradient.html" title="class in org.apache.spark.mllib.optimization">Gradient</a> gradient)</code>
<div class="block">Set the gradient function (of the loss function of one single data example)
to be used for L-BFGS.</div>
</td>
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<tr class="altColor">
<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#setMaxNumIterations(int)">setMaxNumIterations</a></strong>(int iters)</code>
<div class="block"><strong>Deprecated.</strong>
<div class="block"><i>use <a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#setNumIterations(int)"><code>setNumIterations(int)</code></a> instead</i></div>
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<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#setNumCorrections(int)">setNumCorrections</a></strong>(int corrections)</code>
<div class="block">Set the number of corrections used in the LBFGS update.</div>
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<tr class="altColor">
<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#setNumIterations(int)">setNumIterations</a></strong>(int iters)</code>
<div class="block">Set the maximal number of iterations for L-BFGS.</div>
</td>
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<tr class="rowColor">
<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#setRegParam(double)">setRegParam</a></strong>(double regParam)</code>
<div class="block">Set the regularization parameter.</div>
</td>
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<tr class="altColor">
<td class="colFirst"><code><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a></code></td>
<td class="colLast"><code><strong><a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#setUpdater(org.apache.spark.mllib.optimization.Updater)">setUpdater</a></strong>(<a href="../../../../../org/apache/spark/mllib/optimization/Updater.html" title="class in org.apache.spark.mllib.optimization">Updater</a> updater)</code>
<div class="block">Set the updater function to actually perform a gradient step in a given direction.</div>
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<code><a href="../../../../../org/apache/spark/Logging.html#initializeIfNecessary()">initializeIfNecessary</a>, <a href="../../../../../org/apache/spark/Logging.html#initializeLogging()">initializeLogging</a>, <a href="../../../../../org/apache/spark/Logging.html#isTraceEnabled()">isTraceEnabled</a>, <a href="../../../../../org/apache/spark/Logging.html#log_()">log_</a>, <a href="../../../../../org/apache/spark/Logging.html#log()">log</a>, <a href="../../../../../org/apache/spark/Logging.html#logDebug(scala.Function0)">logDebug</a>, <a href="../../../../../org/apache/spark/Logging.html#logDebug(scala.Function0, java.lang.Throwable)">logDebug</a>, <a href="../../../../../org/apache/spark/Logging.html#logError(scala.Function0)">logError</a>, <a href="../../../../../org/apache/spark/Logging.html#logError(scala.Function0, java.lang.Throwable)">logError</a>, <a href="../../../../../org/apache/spark/Logging.html#logInfo(scala.Function0)">logInfo</a>, <a href="../../../../../org/apache/spark/Logging.html#logInfo(scala.Function0, java.lang.Throwable)">logInfo</a>, <a href="../../../../../org/apache/spark/Logging.html#logName()">logName</a>, <a href="../../../../../org/apache/spark/Logging.html#logTrace(scala.Function0)">logTrace</a>, <a href="../../../../../org/apache/spark/Logging.html#logTrace(scala.Function0, java.lang.Throwable)">logTrace</a>, <a href="../../../../../org/apache/spark/Logging.html#logWarning(scala.Function0)">logWarning</a>, <a href="../../../../../org/apache/spark/Logging.html#logWarning(scala.Function0, java.lang.Throwable)">logWarning</a></code></li>
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<h4>LBFGS</h4>
<pre>public LBFGS(<a href="../../../../../org/apache/spark/mllib/optimization/Gradient.html" title="class in org.apache.spark.mllib.optimization">Gradient</a> gradient,
<a href="../../../../../org/apache/spark/mllib/optimization/Updater.html" title="class in org.apache.spark.mllib.optimization">Updater</a> updater)</pre>
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<a name="runLBFGS(org.apache.spark.rdd.RDD, org.apache.spark.mllib.optimization.Gradient, org.apache.spark.mllib.optimization.Updater, int, double, int, double, org.apache.spark.mllib.linalg.Vector)">
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<pre>public static scala.Tuple2<<a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a>,double[]> runLBFGS(<a href="../../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple2<java.lang.Object,<a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a>>> data,
<a href="../../../../../org/apache/spark/mllib/optimization/Gradient.html" title="class in org.apache.spark.mllib.optimization">Gradient</a> gradient,
<a href="../../../../../org/apache/spark/mllib/optimization/Updater.html" title="class in org.apache.spark.mllib.optimization">Updater</a> updater,
int numCorrections,
double convergenceTol,
int maxNumIterations,
double regParam,
<a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a> initialWeights)</pre>
<div class="block">Run Limited-memory BFGS (L-BFGS) in parallel.
Averaging the subgradients over different partitions is performed using one standard
spark map-reduce in each iteration.
<p></div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>data</code> - - Input data for L-BFGS. RDD of the set of data examples, each of
the form (label, [feature values]).</dd><dd><code>gradient</code> - - Gradient object (used to compute the gradient of the loss function of
one single data example)</dd><dd><code>updater</code> - - Updater function to actually perform a gradient step in a given direction.</dd><dd><code>numCorrections</code> - - The number of corrections used in the L-BFGS update.</dd><dd><code>convergenceTol</code> - - The convergence tolerance of iterations for L-BFGS which is must be
nonnegative. Lower values are less tolerant and therefore generally
cause more iterations to be run.</dd><dd><code>maxNumIterations</code> - - Maximal number of iterations that L-BFGS can be run.</dd><dd><code>regParam</code> - - Regularization parameter
<p></dd><dd><code>initialWeights</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>A tuple containing two elements. The first element is a column matrix containing
weights for every feature, and the second element is an array containing the loss
computed for every iteration.</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a> setNumCorrections(int corrections)</pre>
<div class="block">Set the number of corrections used in the LBFGS update. Default 10.
Values of numCorrections less than 3 are not recommended; large values
of numCorrections will result in excessive computing time.
3 < numCorrections < 10 is recommended.
Restriction: numCorrections > 0</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>corrections</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a> setConvergenceTol(double tolerance)</pre>
<div class="block">Set the convergence tolerance of iterations for L-BFGS. Default 1E-4.
Smaller value will lead to higher accuracy with the cost of more iterations.
This value must be nonnegative. Lower convergence values are less tolerant
and therefore generally cause more iterations to be run.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>tolerance</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a> setMaxNumIterations(int iters)</pre>
<div class="block"><span class="strong">Deprecated.</span> <i>use <a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html#setNumIterations(int)"><code>setNumIterations(int)</code></a> instead</i></div>
<div class="block">Set the maximal number of iterations for L-BFGS. Default 100.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>iters</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a> setNumIterations(int iters)</pre>
<div class="block">Set the maximal number of iterations for L-BFGS. Default 100.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>iters</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a> setRegParam(double regParam)</pre>
<div class="block">Set the regularization parameter. Default 0.0.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>regParam</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a> setGradient(<a href="../../../../../org/apache/spark/mllib/optimization/Gradient.html" title="class in org.apache.spark.mllib.optimization">Gradient</a> gradient)</pre>
<div class="block">Set the gradient function (of the loss function of one single data example)
to be used for L-BFGS.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>gradient</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<pre>public <a href="../../../../../org/apache/spark/mllib/optimization/LBFGS.html" title="class in org.apache.spark.mllib.optimization">LBFGS</a> setUpdater(<a href="../../../../../org/apache/spark/mllib/optimization/Updater.html" title="class in org.apache.spark.mllib.optimization">Updater</a> updater)</pre>
<div class="block">Set the updater function to actually perform a gradient step in a given direction.
The updater is responsible to perform the update from the regularization term as well,
and therefore determines what kind or regularization is used, if any.</div>
<dl><dt><span class="strong">Parameters:</span></dt><dd><code>updater</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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<h4>optimize</h4>
<pre>public <a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a> optimize(<a href="../../../../../org/apache/spark/rdd/RDD.html" title="class in org.apache.spark.rdd">RDD</a><scala.Tuple2<java.lang.Object,<a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a>>> data,
<a href="../../../../../org/apache/spark/mllib/linalg/Vector.html" title="interface in org.apache.spark.mllib.linalg">Vector</a> initialWeights)</pre>
<div class="block"><strong>Description copied from interface: <code><a href="../../../../../org/apache/spark/mllib/optimization/Optimizer.html#optimize(org.apache.spark.rdd.RDD, org.apache.spark.mllib.linalg.Vector)">Optimizer</a></code></strong></div>
<div class="block">Solve the provided convex optimization problem.</div>
<dl>
<dt><strong>Specified by:</strong></dt>
<dd><code><a href="../../../../../org/apache/spark/mllib/optimization/Optimizer.html#optimize(org.apache.spark.rdd.RDD, org.apache.spark.mllib.linalg.Vector)">optimize</a></code> in interface <code><a href="../../../../../org/apache/spark/mllib/optimization/Optimizer.html" title="interface in org.apache.spark.mllib.optimization">Optimizer</a></code></dd>
<dt><span class="strong">Parameters:</span></dt><dd><code>data</code> - (undocumented)</dd><dd><code>initialWeights</code> - (undocumented)</dd>
<dt><span class="strong">Returns:</span></dt><dd>(undocumented)</dd></dl>
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